A method of feasible trajectory planning for UAV formation based on bi-directional fast search tree.

This paper mainly studies the obstacle avoidance and rapid reconstruction of UAV formation to improve the adaptability of UAV formation to complex dynamic environment. Firstly, the obstacle and formation constraint model in complex environment are established, and a Bi-directional-Rapidly Exploring Random Tree (Bi-RRT*) algorithm based on greedy strategy is proposed to realize obstacle avoidance, sudden response and formation reconstruction for UAV formation; it improves the efficiency and formation stability of the current optimization algorithm in complex environments. Then, this paper ameliorates the extension of algorithm nodes to improve the efficiency of the solution, the optimization method of nodes growth greatly not only avoid the invalid extension, but also save storage space and improve the convergence speed of the algorithm. In addition, this paper adopts the adaptive step size rolling detection method to improve the sensitivity of the UAV formation to the sudden threat. The experimental results show that the complex environment constraint model proposed in this paper combined with the improved Bi-RRT* algorithm can effectively improve the adaptive ability of UAV formation to the dynamic environment, and it also can plan the ideal trajectory under sudden threats, which greatly improving the survivability of the UAV formation. [ABSTRACT FROM AUTHOR]